David E. Lizdas

27 papers receiving 319 citations

Peers

David E. Lizdas
Comparison fields: 5 of 69
  • Surgery 177
  • Anesthesiology and Pain Medicine 22
  • Human-Computer Interaction 22
  • Computer Vision and Pattern Recognition 68
  • Physiology 66
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Daniel M. Birk United States
Lauryn R. Rochlen United States
Charles V. Edmond United States
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Jeanett J.S. Strandbygaard Denmark
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Citations per year

Countries citing papers authored by David E. Lizdas

Since Specialization
Citations

This map shows the geographic impact of David E. Lizdas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David E. Lizdas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David E. Lizdas more than expected).

Fields of papers citing papers by David E. Lizdas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. Lizdas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David E. Lizdas. The network helps show where David E. Lizdas may publish in the future.

Co-authors

The 25 scholars most cited alongside David E. Lizdas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David E. Lizdas Line = papers co-authored together David E. Lizdas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201354
2 201454
3 201726
4 200826
5 201324
6 201322
7
Transparent Reality: A Simulation Based on Interactive Graphical Models Emphasizing Visualization
200614
8 200513
9 201613
10 201513
11 201310
12 20208
13 20088
14 20166
15 20206
16 20145
17 20155
18 20205
19 20214
20 20194

About David E. Lizdas

David E. Lizdas is a scholar working on Emergency Medicine, Physiology, Critical Care and Intensive Care Medicine, Surgery and Pulmonary and Respiratory Medicine, having authored 29 papers that have together received 335 indexed citations. Recurring topics across this work include Simulation-Based Education in Healthcare (7 papers), Surgical Simulation and Training (6 papers), Cardiac Arrest and Resuscitation (4 papers), Augmented Reality Applications (3 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Intensive Care Unit Cognitive Disorders (3 papers), Advanced Radiotherapy Techniques (2 papers) and Anatomy and Medical Technology (2 papers). The work is most often cited by research in Surgery (177 citations), Anesthesiology and Pain Medicine (22 citations), Human-Computer Interaction (22 citations), Computer Vision and Pattern Recognition (68 citations) and Physiology (66 citations). David E. Lizdas has collaborated with scholars based in United States, Türkiye and Antigua and Barbuda. Frequent co-authors include Samsun Lampotang, Nikolaus L. Gravenstein, Didier A. Rajon, Frank J. Bova, Johanna Lister, Gregory J. A. Murad, William A. Friedman, Ira Fischler, Kristopher G. Hooten and Roshan Jacob. Their work appears in journals such as Simulation in Healthcare The Journal of the Society for Simulation in Healthcare, Anesthesia & Analgesia, Radiation Oncology, Journal of Visualized Experiments and Journal of Wound Ostomy and Continence Nursing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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